An Efficient Multi-keyword top-k Search Scheme over Encrypted Cloud Data
Jian Long Xu, Xinyu Huang, Geng Yang, Yuanyuan Wu · 2018
With the rapid development of cloud computing, an increasing number of data owners are motivated to outsource their sensitive data to cloud servers for flexibility and reduced cost in data management. However, privacy is a big concern for outsourcing data to the cloud, particularly for data sets like health records and financial records which usually contain sensitive information. A practical and widely used technique for data privacy preservation is to encrypt data before outsourcing to the cloud servers. In this case, the retrieval of required files from the encrypted cloud becomes a problem which requires searching over the encrypted data. In this paper, we propose an efficient multi-keyword ranked search scheme over encrypted data in cloud using the data structure group B+ tree. To improve the query efficiency, we construct a B+ tree index structure based on the group of data sets, which can optimize the index structure and provide efficient and fast relevance between the query and cloud data. Specifically, for the privacy concern of query data, we use the improved KNN-based algorithm to encrypt sensitive data; the searchable encryption of this scheme achieves accuracy multi-keyword query over encrypted cloud data and returns the highest relevant top-k results. Extensive experimental results on real-life data sets demonstrate that the proposed approach can significantly reduce the index storage and improve the retrieval efficiency.